Community cancer treatment programs provide care for the majority of cancer patients nationally and could be a large and diverse source of biospecimens for translational cancer research. Unfortunately, community- oriented biorepositories that have access to these patients are limited by a lack of software that meets their needs. Community sites typically have limited resources including IT support and therefore need software that is low cost, easy to install and use, and runs on common hardware and software platforms. Because they are individually low volume, community biorepositories need to be able to contribute to aggregates of comparable biospecimens derived from multiple sites. Production and identification of comparable specimens across sites requires adherence to standard operating procedures, capture of standard data elements, and sharing data across networks of biorepositories. These capabilities exist in sophisticated biorepository software but are not typically found in community-oriented packages. The University of Virginia (UVA) has been developing biorepository software for the past two years for local use by extending the basic biorepository module included with the open source research data management system, Caisis. Caisis was originally developed with NCI funding at Memorial Sloan Kettering Cancer Center. It is a .Net application that uses Microsoft SQL Server as a back end. It can be installed on a single Windows server and is straightforward to administer and use. The system has an active open source user and developer community, of which UVA is a member, and commercial support is available as an option. UVA and a collaborating group of community-oriented biorepositories propose to extend UVA's initial work on the Caisis biospecimen module to create a modern biorepository system that is appropriate for community sites. The resulting software will support the full complement of biorepository activities, including protocol-driven specimen collection and archival biobanking using current recommendations for biorepository standard operating procedures and current biorepository data standards. It will support clinical annotation, quality control workflows, specimen search based on processing or clinical characteristics, and specimen request and distribution tracking. It will also support sharing specimen and request information between systems using standard communication protocols. The software will be written at UVA over a two year period and progressive releases with test plans will be installed and evaluated at the partner community sites. In the final year of the project, documentation of the data model, an installation/ maintenance guide, and a user guide will be written and the software and documentation will be packaged and contributed to the Caisis open source project.